We introduce a model of a platform in which users encounter news of unknown veracity. Users vary in their propensity to share news and can learn the veracity of news at a cost. In turn, the production of fake news is both more sensitive to sharing rates and cheaper than its truthful counterpart. As in traditional markets, the prevalence of fake news is determined by a demand and a supply of misinformation. Unlike traditional markets, the exercise of market power is generally limited unless segmentation methods are employed. Combating fake news by lowering verification costs can be ineffective due to the demand for misinformation only weakly reducing, while the use of algorithms that imperfectly filter news for users can lead to more prevalence and diffusion of misinformation. Our findings highlight the important role that natural elasticity measures have for policy evaluation.
We consider learning and signaling in a dynamic Cournot oligopoly where firms have private information about their production costs and only observe the market price, which is subject to unobservable demand shocks. An equilibrium is Markov if play depends on the history only through the firms’ beliefs about costs and calendar time. We characterize symmetric linear Markov equilibria as solutions to a boundary value problem. In every such equilibrium, given a long enough horizon, play converges to the static complete information outcome for the realized costs, but each firm only learns its competitors’ average cost. The weights assigned to costs and beliefs under the equilibrium strategies are non-monotone over time. This can be explained by decomposing incentives into signaling and learning, and discuss implications for prices, quantities, and welfare.
We characterize the optimal mechanism and investment level in an environment where (i) two projects of independent costs are purchased sequentially, (ii) the buyer can commit to a two‐period mechanism, and (iii) the winner of the first project can invest in a cost‐reducing technology between auctions. We show that, in an attempt to induce more competition in the first period, the optimal mechanism gives an advantage to the first‐period winner in the second auction. As a result of this advantage, the first‐period winner invests more than the socially efficient level. Optimal advantages, therefore, create two different channels for cost minimization in buyer‐supplier relationships.
We find a sufficient condition such that a distributional upgrade on a seller’s cost distribution implies a lower expected procurement cost for a buyer. We also show that even under the strongest assumption about this upgrade made in the literature so far, the seller can be worse off, even if this upgrade is costless.
I have a new working paper titled “Fake News in Social Media: A Supply and Demand Approach”